End of training

README.md

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+---
+license: mit
+base_model: microsoft/deberta-v3-small
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: deberta-v3-small-nslp-forc-subtask1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# deberta-v3-small-nslp-forc-subtask1
+
+This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2167
+- Accuracy: 0.6649
+- Precision: 0.6642
+- Recall: 0.6649
+- F1-weighted: 0.6595
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1-weighted |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:-----------:|
+| 0.3563        | 0.77  | 2000  | 0.3333          | 0.5035   | 0.4651    | 0.5035 | 0.4562      |
+| 0.2443        | 1.54  | 4000  | 0.2647          | 0.5708   | 0.5598    | 0.5708 | 0.5484      |
+| 0.1736        | 2.31  | 6000  | 0.2359          | 0.6152   | 0.6105    | 0.6152 | 0.5969      |
+| 0.1404        | 3.08  | 8000  | 0.2207          | 0.6424   | 0.6391    | 0.6424 | 0.6250      |
+| 0.1109        | 3.85  | 10000 | 0.2181          | 0.6581   | 0.6534    | 0.6581 | 0.6490      |
+| 0.0817        | 4.62  | 12000 | 0.2167          | 0.6649   | 0.6642    | 0.6649 | 0.6595      |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.2
+- Datasets 2.17.0
+- Tokenizers 0.15.1

added_tokens.json

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config.json

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